EVENT GRAPHS: ADVANCES AND APPLICATIONS OF SECOND-ORDER TIME-UNFOLDED TEMPORAL NETWORK MODELS

Recent advances in data collection and storage have allowed both researchers and industry alike to collect data in real time. Much of this data comes in the form of ‘events’, or timestamped interactions, such as email and social media posts, website clickstreams, or protein–protein interactions. This type of data poses new challenges for modeling, especially if we wish to preserve all temporal features and structure. We highlight several recent approaches in modeling higher-order temporal interaction and bring them together under the umbrella of event graphs. Through examples, we demonstrate how event graphs can be used to understand the higher-order topological-temporal structure of temporal networks and capture properties of the network that are unobservable when considering either a static (or time-aggregated) model. We introduce new algorithms for temporal motif enumeration and provide a novel analysis of the communicability centrality for temporal networks. Furthermore, we show that by modeling a temporal network as an event graph our analysis extends easily to non-dyadic interactions, known as hyper-events.

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MLL Translocation Partners AF4, AF5q31, and ENL Associate in a Higher Order Protein Complex with CDK9 and Cyclin T1.

Blood ◽

10.1182/blood.v106.11.99.99 ◽

2005 ◽

Vol 106 (11) ◽

pp. 99-99

Author(s):

Min Lin ◽

Michael L. Cleary

Keyword(s):

Western Blotting ◽

Protein Interactions ◽

Protein Complex ◽

Fusion Proteins ◽

Higher Order ◽

Chromosomal Translocations ◽

Transcriptional Elongation ◽

Protein Protein Interactions ◽

Methyltransferase Activity ◽

Cyclin T1

Abstract The Mixed Lineage Leukemia (MLL) gene is frequently involved in chromosomal translocations that cause acute leukemia. More than 40 different genes have been identified as MLL translocation partners, with the expression of corresponding MLL fusion proteins. The MLL protein has histone methyltransferase activity and is required for embryonic development and hematopoiesis. Several proteins have been demonstrated to associate with MLL in a macromolecular complex, which is believed to have chromatin remodeling function. However, the C-terminal SET domain of MLL, which carries the histone methyltransferase activity, is lost in all MLL fusion proteins, thus making the biochemical functions of the fusion proteins unclear. Moreover, the promiscuity of MLL translocation partners, most of them with no known functions, further complicates an understanding of MLL leukemogenic mechanisms. In this study, we purified a protein complex containing AF4, the most common MLL translocation partner, using a combination of conventional column chromatography and immunoaffinity techniques. The AF4 protein complex contains AF5q31 and ENL, two other MLL translocation partners, as well as CDK9 and Cyclin T1, a heterodimer that regulates transcriptional elongation. Gel filtration confirmed that these five proteins co-fractionate with an estimated overall size of 0.8 MDa. All protein-protein interactions were further confirmed by immunoprecipitation-western blotting from K562 cell nuclear extract. To investigate whether these protein-protein interactions are retained in corresponding MLL fusion proteins, immunoprecipitation-western blotting assays were carried out in human leukemia cell lines harboring MLL chromosomal translocations. We found that MLL-AF4, MLL-AF5q31, MLL-ENL and MLL-AF9 each associate with wild type AF4 complex components, including CDK9 and Cyclin T1. In contrast, MLL-AF6 does not associate with any of the AF4 complex components. We propose that the four nuclear MLL translocation partner proteins (AF4, AF5q31, ENL/AF9), whose translocations are found in over 75% of MLL leukemias, associate in a higher order protein complex with CDK9 and Cyclin T1 and thus function in part to regulate transcriptional elongation. The association of CDK9 and Cyclin T1 with the four MLL fusion proteins suggests a common leukemogenic mechanism that may involve transcriptional elongation, which we are currently investigating. Conversely, MLL-cytosolic fusions, e.g. MLL-AF6, appear to function independently of association with the AF4 protein complex, possibly through a homo-dimerization pathway.

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Inferring cell cycle phases from a partially temporal network of protein interactions

10.1101/2021.03.26.437187 ◽

2021 ◽

Author(s):

Maxime Lucas ◽

Arthur Morris ◽

Alex Townsend-Teague ◽

Laurent Tichit ◽

Bianca H Habermann ◽

...

Keyword(s):

Cell Cycle ◽

Protein Interactions ◽

Time Series Data ◽

A Priori ◽

Biological Systems ◽

Series Data ◽

Biological Knowledge ◽

Temporal Network ◽

Protein Protein Interactions ◽

Temporal Organisation

The temporal organisation of biological systems into phases and subphases is often crucial to their functioning. Identifying this multiscale organisation can yield insight into the underlying biological mechanisms at play. To date, however, this identification requires a priori biological knowledge of the system under study. Here, we recover the temporal organisation of the cell cycle of budding yeast into phases and subphases, in an automated way. To do so, we model the cell cycle as a partially temporal network of protein-protein interactions (PPIs) by combining a traditional static PPI network with protein concentration or RNA expression time series data. Then, we cluster the snapshots of this temporal network to infer phases, which show good agreement with our biological knowledge of the cell cycle. We systematically test the robustness of the approach and investigate the effect of having only partial temporal information. The generality of the method makes it suitable for application to other, less well-known biological systems for which the temporal organisation of processes plays an important role.

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Rapamycin-dependent delocalization as a novel tool to reveal protein-protein interactions in plants

10.1101/2020.03.09.983270 ◽

2020 ◽

Author(s):

Joanna Winkler ◽

Evelien Mylle ◽

Andreas De Meyer ◽

Benjamin Pavie ◽

Julie Merchie ◽

...

Keyword(s):

Plant Cell ◽

High Throughput ◽

Protein Interactions ◽

Biological Process ◽

Higher Order ◽

Protein Protein Interactions ◽

Bait Protein ◽

Versatile Tool ◽

Protein Tagging

AbstractIdentifying protein-protein interactions (PPI) is crucial to understand any type of biological process. Many PPI tools are available, yet only some function within the context of a plant cell. Narrowing down even further, only few PPI tools allow visualizing higher order interactions. Here, we present a novel and conditional in vivo PPI tool for plant research. Knocksideways in plants (KSP) uses the ability of rapamycin to alter the localization of a bait protein and its interactors via the heterodimerization of FKBP and FRB domains. KSP is inherently free from many limitations, which other PPI systems hold. It is an in vivo tool, it is flexible concerning the orientation of protein tagging as long as this does not interfere with the interaction and it is compatible with a broad range of fluorophores. KSP is also a conditional tool and therefore does not require additional controls. The interactions can be quantified and in high throughput by the scripts that we provide. Finally, we demonstrate that KSP can visualize higher-order interactions. It is therefore a versatile tool, complementing the PPI methods field with unique characteristics and applications.

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The effect of nanoscale surface curvature on the oligomerization of surface-bound proteins

Journal of The Royal Society Interface ◽

10.1098/rsif.2013.0818 ◽

2014 ◽

Vol 11 (94) ◽

pp. 20130818 ◽

Cited By ~ 23

Author(s):

M. Kurylowicz ◽

H. Paulin ◽

J. Mogyoros ◽

M. Giuliani ◽

J. R. Dutcher

Keyword(s):

Single Molecule ◽

Protein Interactions ◽

Protein Function ◽

Higher Order ◽

Surface Curvature ◽

Protein Protein Interactions ◽

Single Molecule Force Spectroscopy ◽

Adsorbed Proteins ◽

Β Lactoglobulin

The influence of surface topography on protein conformation and association is used routinely in biological cells to orchestrate and coordinate biomolecular events. In the laboratory, controlling the surface curvature at the nanoscale offers new possibilities for manipulating protein–protein interactions and protein function at surfaces. We have studied the effect of surface curvature on the association of two proteins, α-lactalbumin (α-LA) and β-lactoglobulin (β-LG), which perform their function at the oil–water interface in milk emulsions. To control the surface curvature at the nanoscale, we have used a combination of polystyrene (PS) nanoparticles (NPs) and ultrathin PS films to fabricate chemically pure, hydrophobic surfaces that are highly curved and are stable in aqueous buffer. We have used single-molecule force spectroscopy to measure the contour lengths L c for α-LA and β-LG adsorbed on highly curved PS surfaces (NP diameters of 27 and 50 nm, capped with a 10 nm thick PS film), and we have compared these values in situ with those measured for the same proteins adsorbed onto flat PS surfaces in the same samples. The L c distributions for β-LG adsorbed onto a flat PS surface contain monomer and dimer peaks at 60 and 120 nm, respectively, while α-LA contains a large monomer peak near 50 nm and a dimer peak at 100 nm, with a tail extending out to 200 nm, corresponding to higher order oligomers, e.g. trimers and tetramers. When β-LG or α-LA is adsorbed onto the most highly curved surfaces, both monomer peaks are shifted to much smaller values of L c . Furthermore, for β-LG, the dimer peak is strongly suppressed on the highly curved surface, whereas for α-LA the trimer and tetramer tail is suppressed with no significant change in the dimer peak. For both proteins, the number of higher order oligomers is significantly reduced as the curvature of the underlying surface is increased. These results suggest that the surface curvature provides a new method of manipulating protein–protein interactions and controlling the association of adsorbed proteins, with applications to the development of novel biosensors.

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Evolution and emergence: higher order information structure in protein interactomes across the tree of life

Integrative Biology ◽

10.1093/intbio/zyab020 ◽

2021 ◽

Author(s):

Brennan Klein ◽

Erik Hoel ◽

Anshuman Swain ◽

Ross Griebenow ◽

Michael Levin

Keyword(s):

Protein Interactions ◽

Biological Networks ◽

Information Structure ◽

Regulatory Networks ◽

Biological Systems ◽

Higher Order ◽

Protein Protein Interactions ◽

Black Boxes ◽

Sensitivity Tests ◽

Network Simulations

Abstract The internal workings of biological systems are notoriously difficult to understand. Due to the prevalence of noise and degeneracy in evolved systems, in many cases the workings of everything from gene regulatory networks to protein–protein interactome networks remain black boxes. One consequence of this black-box nature is that it is unclear at which scale to analyze biological systems to best understand their function. We analyzed the protein interactomes of over 1800 species, containing in total 8 782 166 protein–protein interactions, at different scales. We show the emergence of higher order ‘macroscales’ in these interactomes and that these biological macroscales are associated with lower noise and degeneracy and therefore lower uncertainty. Moreover, the nodes in the interactomes that make up the macroscale are more resilient compared with nodes that do not participate in the macroscale. These effects are more pronounced in interactomes of eukaryota, as compared with prokaryota; these results hold even after sensitivity tests where we recalculate the emergent macroscales under network simulations where we add different edge weights to the interactomes. This points to plausible evolutionary adaptation for macroscales: biological networks evolve informative macroscales to gain benefits of both being uncertain at lower scales to boost their resilience, and also being ‘certain’ at higher scales to increase their effectiveness at information transmission. Our work explains some of the difficulty in understanding the workings of biological networks, since they are often most informative at a hidden higher scale, and demonstrates the tools to make these informative higher scales explicit.

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Corynebacterium glutamicum Regulation beyond Transcription: Organizing Principles and Reconstruction of an Extended Regulatory Network Incorporating Regulations Mediated by Small RNA and Protein–Protein Interactions

Microorganisms ◽

10.3390/microorganisms9071395 ◽

2021 ◽

Vol 9 (7) ◽

pp. 1395

Author(s):

Juan M. Escorcia-Rodríguez ◽

Andreas Tauch ◽

Julio A. Freyre-González

Keyword(s):

Corynebacterium Glutamicum ◽

Protein Interactions ◽

Regulatory Network ◽

Regulatory Networks ◽

Network Models ◽

Global Scale ◽

System Level ◽

Model Organisms ◽

Protein Protein Interactions ◽

Regulatory Structure

Corynebacterium glutamicum is a Gram-positive bacterium found in soil where the condition changes demand plasticity of the regulatory machinery. The study of such machinery at the global scale has been challenged by the lack of data integration. Here, we report three regulatory network models for C. glutamicum: strong (3040 interactions) constructed solely with regulations previously supported by directed experiments; all evidence (4665 interactions) containing the strong network, regulations previously supported by nondirected experiments, and protein–protein interactions with a direct effect on gene transcription; sRNA (5222 interactions) containing the all evidence network and sRNA-mediated regulations. Compared to the previous version (2018), the strong and all evidence networks increased by 75 and 1225 interactions, respectively. We analyzed the system-level components of the three networks to identify how they differ and compared their structures against those for the networks of more than 40 species. The inclusion of the sRNA-mediated regulations changed the proportions of the system-level components and increased the number of modules but decreased their size. The C. glutamicum regulatory structure contrasted with other bacterial regulatory networks. Finally, we used the strong networks of three model organisms to provide insights and future directions of the C.glutamicum regulatory network characterization.

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Insights into Conformational Dynamics and Allostery in DNMT1-H3Ub/USP7 Interactions

Molecules ◽

10.3390/molecules26175153 ◽

2021 ◽

Vol 26 (17) ◽

pp. 5153

Author(s):

Yu Zhu ◽

Fei Ye ◽

Ziyun Zhou ◽

Wanlin Liu ◽

Zhongjie Liang ◽

...

Keyword(s):

Pathway Analysis ◽

Protein Interactions ◽

Molecular Mechanisms ◽

Network Modeling ◽

Conformational Dynamics ◽

Network Models ◽

Dna Methyltransferases ◽

Protein Protein Interactions ◽

Mutational Hotspots ◽

Dynamics Simulations

DNA methyltransferases (DNMTs) including DNMT1 are a conserved family of cytosine methylases that play crucial roles in epigenetic regulation. The versatile functions of DNMT1 rely on allosteric networks between its different interacting partners, emerging as novel therapeutic targets. In this work, based on the modeling structures of DNMT1-ubiquitylated H3 (H3Ub)/ubiquitin specific peptidase 7 (USP7) complexes, we have used a combination of elastic network models, molecular dynamics simulations, structural residue perturbation, network modeling, and pocket pathway analysis to examine their molecular mechanisms of allosteric regulation. The comparative intrinsic and conformational dynamics analysis of three DNMT1 systems has highlighted the pivotal role of the RFTS domain as the dynamics hub in both intra- and inter-molecular interactions. The site perturbation and network modeling approaches have revealed the different and more complex allosteric interaction landscape in both DNMT1 complexes, involving the events caused by mutational hotspots and post-translation modification sites through protein-protein interactions (PPIs). Furthermore, communication pathway analysis and pocket detection have provided new mechanistic insights into molecular mechanisms underlying quaternary structures of DNMT1 complexes, suggesting potential targeting pockets for PPI-based allosteric drug design.

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Corynebacterium Glutamicum Regulation beyond Transcription: Organizing Principles and Reconstruction of an Extended Regulatory Network Incorporating Regulations Mediated by Small Rna and Protein-Protein Interactions

10.20944/preprints202012.0503.v1 ◽

2020 ◽

Author(s):

Juan M. Escorcia-Rodríguez ◽

Andreas Tauch ◽

Julio A. Freyre-González

Keyword(s):

Corynebacterium Glutamicum ◽

Protein Interactions ◽

Regulatory Network ◽

Transcriptional Regulatory Network ◽

Network Models ◽

Global Scale ◽

System Level ◽

Model Organisms ◽

Protein Protein Interactions ◽

Regulatory Structure

Corynebacterium glutamicum is a Gram-positive bacterium found in soil where the condition changes demand plasticity of the regulatory interactions, which study at the global scale has been challenged by the lack of data integration. Here, we update the manually-curated C. glutamicum transcriptional regulatory network, now including protein-protein interactions having a direct effect on gene transcription. The network model with regulations supported by any experimental evidence increased by 557 interactions regarding the previous (2018) version. 73 interactions supported by directed experiments were also included in a second model. We included 545 sRNA-mediated regulations in a third model with a total of 5164 interactions. We deposited the three network models in Abasy Atlas v2.4. We study the C. glutamicum regulatory structure by comparing it against the networks for more than 40 species, finding it to contrast in several global structural properties. We analyze the system-level components of the networks, finding that the inclusion of the sRNAs regulations changes their proportions, transferring part of the basal machinery to the modular class and increasing the number of modules while decreasing their size. Finally, we use strong networks of three model organisms to provide insights in future directions of the C. glutamicum network characterization.

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Corynebacterium glutamicum regulation beyond transcription: Organizing principles and reconstruction of an extended regulatory network incorporating regulations mediated by small RNA and protein-protein interactions

10.1101/2021.01.07.423633 ◽

2021 ◽

Author(s):

Juan Miguel Escorcia-Rodríguez ◽

Andreas Tauch ◽

Julio Augusto Freyre-González

Keyword(s):

Corynebacterium Glutamicum ◽

Protein Interactions ◽

Regulatory Network ◽

Regulatory Networks ◽

Network Models ◽

Global Scale ◽

System Level ◽

Model Organisms ◽

Protein Protein Interactions ◽

Regulatory Structure

Corynebacterium glutamicum is a Gram-positive bacterium found in soil where the condition changes demand plasticity of the regulatory machinery. The study of such machinery at the global scale has been challenged by the lack of data integration. Here, we report three regulatory network models for C. glutamicum: strong (3040 interactions) constructed solely with regulations previously supported by directed experiments; all evidence (4665 interactions) containing the strong network, regulations previously supported by non-directed experiments, and protein-protein interactions with a direct effect on gene transcription; and sRNA (5222 interactions) containing the all evidence network and sRNA-mediated regulations. Compared to the previous version (2018), the strong and all evidence networks increased by 75 and 1225 interactions, respectively. We analyzed the system-level components of the three networks to identify how they differ and compared their structures against those for the networks of more than 40 species. The inclusion of the sRNAs regulations changed the proportions of the system-level components and increased the number of modules but decreased their size. The C. glutamicum regulatory structure contrasted with other bacterial regulatory networks. Finally, we used the strong networks of three model organisms to provide insights and future directions of the C. glutamicum regulatory network characterization.

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